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Estimating Semiparametric and Nonparametric Fixed Effects Panel Data Models with mgcv

Ivan Korolev

arXiv 10 Jun 2026 · Econometrics

arXiv:2606.12739 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper provides a practical guide to estimating semiparametric and nonparametric fixed-effects panel data models using the mgcv package in R. The focus is implementation: handling fixed effects with unit indicators, first differencing, or penalized unit effects; specifying smooth terms; and conducting cluster-robust inference. Monte Carlo experiments compare \code{mgcv::bam} estimators with linear and fixed-series spline estimators. Simulations suggest that penalized splines adapt to unknown smoothness and estimate functions accurately in the designs studied here. A penalty-adjusted cluster-robust covariance estimator yields tests with near-nominal size for finite-dimensional parameters, and confidence bands provide accurate coverage for centered unknown functions.

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Cameron, A. Colin and Miller, Douglas L (2015) A Practitioner's Guide to Cluster-Robust Inference0.64422100%
2Marra, Giampiero and Wood, Simon N (2012) Coverage Properties of Confidence Intervals for Generalized Additive Model Components0.64422100%
3Wood, Simon N (2003) Thin-Plate Regression Splines0.64422100%
4Wood, Simon N (2011) Fast Stable Restricted Maximum Likelihood and Marginal Likelihood Estimation of Semiparametric Generalized Linear Models0.64422100%
5Ai, Chunrong and Chen, Xiaohong (2003) Efficient Estimation of Models with Conditional Moment Restrictions Containing Unknown Functions0.40511100%
6An, Yonghong and Hsiao, Cheng and Li, Dong (2016) Semiparametric Estimation of Partially Linear Varying Coefficient Panel Data Models0.40511100%
7Arellano, Manuel (1987) Computing Robust Standard Errors for Within-Groups Estimators0.40511100%
8Baglan, Deniz and Yoldas, Emre (2014) Non-Linearity in the Inflation-Growth Relationship in Developing Economies: Evidence from a Semiparametric Panel Model0.40511100%
9Baltagi, Badi H. and Li, Dong (2002) Series Estimation of Partially Linear Panel Data Models with Fixed Effects0.40511100%
10Borri, Karine T. and Martins-Filho, Carlos and Kalatzis, Aquiles E. G (2022) Exploring Nonlinearities Between Investment and Internal Funds: Evidence of the U-Shaped Investment Curve0.40511100%

Showing the top 10 of 23 scored citations.